Having a busy summer, as always, but here’s a brief note: typos are a problem for machine translators. The best ones (like DeepL) have some ability to recognize typos and correct for them. But they usually can’t do that when the typo is a correctly spelled word (just not the one you intended to type).… Continue reading Typos + MT
Category: Machine translation
Elderberry Hot
Machine translation systems still have trouble recognizing proper names. Recently I was proofreading English texts for an Austrian museum and came across a line that went something like this: The project was directed by Thomas Schmidt and Elderberry Hot. Now, a lot of the texts I work with are about artists and some of them… Continue reading Elderberry Hot
Human or MT: you decide
How to play: Have a look at this essay: https://www.bachelorandmaster.com/creationofknowledge/myth-of-sisyphus.html Try to determine whether it was produced by a human being or translation software. Tell me in the comments which one you think it was, and why.
When bad translations are good
Today I ran across an example of a category most people don’t know about: extremely close translations for opera singers. I say “close” rather than “literal” because it’s not just about communicating the exact meaning, but also keeping words in mostly the same order so that you could basically nail the target sentence on top… Continue reading When bad translations are good
Deadly MT
I often run legal boilerplate (with all specifics of the case removed) through DeepL as a preliminary measure. Today’s experiment was from an alimony contract. And I’m pretty sure the person who signed it didn’t intend to agree to this: Because of the fulfilment of the obligations arising from this document, I submit myself to… Continue reading Deadly MT
Interlingual puns
Some people seem to think (see this post) that a really great machine-translation program would be able to “handle complicated multilingual puns with ease.” But what is a “multilingual pun” anyway? The prefix “multi” implies more than two, and honestly, off the top of my head I can’t think of any puns involving more than… Continue reading Interlingual puns
Puns and jokes
In this post I promised to go through some pun-translation strategies. What makes puns hard to translate is that there is almost never one “right” or “best” solution. Puns give rise to several different scenarios: 1. You just translate the straight meaning and write a footnote about how it was a pun in the source… Continue reading Puns and jokes
That’s pathetic
Here’s the start of a German sentence I’m working on right now: Die überwältigende Musik in Kombination mit kurzen, pathetisch vorgetragenen Deklarationen von hehren Zielen … And here’s how the best free machine translator renders it into English: The overwhelming music combined with short, pathetic declarations of noble goals … But according to dict.cc, “pathetisch”… Continue reading That’s pathetic
How good can MT get?
Over at Slate Star Codex, Scott Alexander has a good post about the future of AI, but I need to nitpick these speculations about what a “future superintelligent Google Translate” could do: For example, take Google Translate. A future superintelligent Google Translate would be able to translate texts faster and better than any human translator,… Continue reading How good can MT get?
Find the difference
People tend to think of machine-translation post editing as “easier” than old-fashioned translation. But I’ve come to think of MTPE not as easier than traditional translation, but as requiring a different set of skills. Namely, the same skills required by find-the-difference puzzles. Find-the-difference puzzles vary in difficulty, of course, just as MT jobs do. You… Continue reading Find the difference